DeepSeek-Coder-V2-Lite-Instruct-GGUF

Instructions to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF",
	filename="DeepSeek-Coder-V2-Lite-Instruct-IQ3_M.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M

Ollama
How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Ollama:
```
ollama run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
```

Unsloth Studio

How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting

Docker Model Runner
How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.DeepSeek-Coder-V2-Lite-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

"llama.cpp error: 'error loading model architecture: unknown model architecture: 'deepseek2''"

by ZeroCool22 - opened Jun 26, 2024

Discussion

ZeroCool22

Jun 26, 2024

{
  "title": "Failed to load model",
  "cause": "llama.cpp error: 'error loading model architecture: unknown model architecture: 'deepseek2''",
  "errorData": {
    "n_ctx": 8192,
    "n_batch": 512,
    "n_gpu_layers": 31
  },
  "data": {
    "memory": {
      "ram_capacity": "31.91 GB",
      "ram_unused": "26.74 GB"
    },
    "gpu": {
      "gpu_names": [
        "NVIDIA GeForce GTX 1080 Ti"
      ],
      "vram_recommended_capacity": "11.00 GB",
      "vram_unused": "9.98 GB"
    },
    "os": {
      "platform": "win32",
      "version": "10.0.19045",
      "supports_avx2": true
    },
    "app": {
      "version": "0.2.24",
      "downloadsDir": "C:\\Users\\ZeroCool22\\.cache\\lm-studio\\models"
    },
    "model": {}
  }
}```